Bounding systems: A qualitative study exploring healthcare coordination between the emergency youth shelter system and health system in Toronto, Canada
Bibliographic record
Abstract
BACKGROUND: Several youth staying at emergency youth shelters (EYSs) in Toronto experience poorly coordinated care for their health needs, as both the EYS and health systems operate largely in silos when coordinating care for this population. Understanding how each system is structurally and functionally bound in their healthcare coordination roles for youth experiencing homelessness (YEH) is a preliminary step to identify how healthcare coordination can be strengthened using a system thinking lens, particularly through the framework for transformative system change. METHODS: Forty-six documents, and twenty-four semi-structured interviews were analyzed to explore how the EYS and health systems are bound in their healthcare coordination roles. We continuously compared data collected from documents and interviews using constant comparative analysis to build a comprehensive understanding of each system's layers, and the niches (i.e., programs and activities), organizations and actors within these layers that contribute to the provision and coordination of healthcare for YEH, within and between these two systems. RESULTS: The EYS and health systems are governed by different ministries, have separate mandates, and therefore have distinct layers, niches, and organizations respective to coordinating healthcare for YEH. While neither system takes sole responsibility for this task, several government, research, and community-based efforts exist to strengthen healthcare coordination for this population, with some overlap between systems. Several organizations and actors within each system are collaborating to develop relevant frameworks, policies, and programs to strengthen healthcare coordination for YEH. Findings indicate that EYS staff play a more active role in coordinating care for YEH than health system staff. CONCLUSION: A vast network of organizations and actors within each system layer, work both in silos and collaboratively to coordinate health services for YEH. Efforts are being made to bridge the gap between systems to improve healthcare coordination, and thereby youths' health outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.025 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".